A power amplifier (PA) is inherently non-linear in nature. When used in a wireless transmitter, a PA's non-linearity generates spectral regrowth, which leads to adjacent channel interference and violations of the out-of-band emission requirements mandated by regulatory authorities. The non-linearity also causes in-band distortion, which degrades the transmitter's Bit Error Rate (BER). Referring to FIG. 1, predistortion is a technique which compensates for PA non-linearity by processing a signal x(n) with a predistortion device (PD) 10, prior to amplification by the PA 12. The PD 10 has inverse characteristics to the PA 12. Thus, pre-processing the signal x(n) by the PD 10 effectively neutralises the non-linearities of the PA 12.
The parameters of a PA can vary (e.g. with changes in supply voltage, temperature etc.) and the PD must be adaptable to those changes. Adaptive PreDistortion (APD) systems for wireless handsets are constrained to use economical (low cost and size) adaptation engines such as the Least Means Squared (LMS) engine to train the PD. The LMS engine employs a constant ‘learning factor’ that must be chosen to satisfy both convergence speed and noise rejection. Accordingly, as the noise level in a signal increases, the learning factor must be turned down, thereby compromising convergence speed. However, as the convergence speed drops, key specifications (e.g. switching output RF spectrum [ORFS, output radio frequency spectrum] etc.) can fail when the PA distortion characteristics change.
Many conventional APD systems are based on memory-less models for both the PA and the PD. However, PAs manifest time-dependent memory effects (i.e. PA memory). Thus, in chasing PA memory effects, conventional memory-less APD systems experience noisy PD gain updates (as shown in FIG. 2).
An APD requires a feedback path to detect or measure how the APD is performing compared to an ideal transmitter signal. This detector consists of, for example, a coupler, a down converter, and an ADC, which in addition to measuring the APD performance also acts as a receiver. Given that the detector LO will be incoherent with any blockers or interferers received, the resultant down converted, baseband signal will manifest as noise. Unless preventive measures are taken, the increase in receiver noise can be transferred to the wireless transmitter, thereby degrading the transmitter Carrier to Interference Plus Noise Ratio [CINR]. In other words, adjacent channel interference and PA memory effects manifest as additional noise sources, which when combined with underlying circuit noise in a wireless transmitter causes the overall performance of the transmitter to suffer (e.g. degraded ORFS performance and CINR). Further, in providing immunity to the additional noise, the LMS learning factor in a conventional APD system may need to be detuned so much that convergence of the PD is critically compromised.
WO 01/29963 mentions Recursive Least Squares (RLS) as a faster converging algorithm for predistortion than LMS. Y. Doo Kim et al, Vehicular Technology Conference 2006, VTC 2006 Spring, IEEE 63rd, Vol 5, P. 2290-2293 describes a generalised polynomial based RLS algorithm for solving a predistortion and quadrature compensation problem.